Residential C[O.sub.2] Emissions in Europe and Carbon Taxation: A Country-Level Assessment.

• Date: 01 September 2023
• Author: Charlier, Dorothee

1. INTRODUCTION

   According to European Environment Agency (2020), EU greenhouse gas emissions decreased by 2% in 2018, but this promising trend is still insufficient, for at least two reasons. First, emissions covered by the European Union Emissions Trading Scheme (EU ETS) have effectively decreased, but those not covered by the EU ETS have not changed significantly. Secondly, the EU 2030 climate and energy framework sets a binding target to cut emissions by at least 40% below 1990 levels by 2030. The residential sector accounts for around 20% of European C[O.sub.2] emissions, with energy demand mainly driven by heating (Eurostat, 2019). (1) Because emissions from the residential sector cannot be displaced, climate policies could be effective but a clear understanding of their consequences is required.

   The first objective of this paper is to study the determinants of residential C[O.sub.2] emissions in Europe. We used panel data for 19 European countries from 2000-2017 and reveal huge differences between countries' C[O.sub.2] emissions. We first estimated a static model that assumes an instantaneous adjustment of C[O.sub.2] emissions per capita to changes in energy prices, income and heating needs. We then extended this model to account for dynamic adjustments and computed short-term and longterm elasticities of per capita C[O.sub.2] emissions relative to each driver. Our results show strong relationships between C[O.sub.2] emissions per capita, GDP per capita, energy prices and heating needs. We found that the income elasticity of C[O.sub.2] emissions per capita is not constant and depends on the level of GDP per capita. When instantaneous adjustment is assumed, the elasticities of per capita C[O.sub.2] emissions relative to natural gas and heating-oil prices are found to be -0.23 and -0.14 respectively. The corresponding short-term elasticities from dynamic models are -0.12 and -0.11, and the longterm elasticities estimated to be -0.47 and -0.38. Our results are in line with those from studies analyzing the determinants of energy demand in the residential sector. Although these studies did not focus on C[O.sub.2] emissions, they report elasticities significantly positive and lower than one for income and negative for prices, with values between -1.7 and -0.04. We also confirm that C[O.sub.2] emissions per capita increase with heating needs, the short-run elasticities fall between 0.77 and 0.85, and the corresponding long-run elasticities are three times higher.

   Our second objective is to examine whether the carbon tax can be an effective complement to the EU ETS for emissions that remain unregulated, like those from the residential sector. We measured the consequences of the tax on C[O.sub.2] emissions and how the burden of this tax is distributed among countries. Imposing a European carbon tax could increase the regressive properties of carbon taxation, which could result in a popular rejection of the policy. (2) Our econometric estimates were used to predict which countries would bear the largest increase in energy prices from a European carbon tax. We assumed a 100% pass-through rate of the tax into energy prices and assessed the short-term impacts of the tax policy. We confirmed that this tax leads to inequalities in the tax burden, as measured by the ratio of tax revenues to GDP by country. Our simulations show for example that a carbon tax of [euro]20 per tonne represents 0.02% of Danish GDP but 0.17% of that of Poland in terms of tax revenue. These differences in the tax burden, highlighted in previous works (see Metcalf et al. (2008) or Hasset et al. (2009) for example), may be a limit to the effectiveness of the policy. For instance, Borozan (2019) found that the tax has little effect on the energy consumption of rich households, and redistribution targeted at poor households increases their consumption. He showed that the carbon tax policy may be ineffective or even counterproductive. Finally, we propose a policy that may correct for these inequalities. It consists of the redistribution of carbon tax revenues in order to obtain, ex-post, an equal tax-to-GDP ratio among all countries. We show that the main beneficiaries would be Poland, the Czech Republic and Belgium, while Denmark, Spain and Luxembourg would have to pay a surtax.

   The remainder of the paper is structured as follows: Section 2 contains a brief literature review on energy demand drivers, C[O.sub.2] emissions and carbon taxation in the residential sector. Section 3 describes the data used. Section 4 presents the methodological approach and Section 5 the empirical findings. The simulation results of the carbon tax policy are contained in Section 6. Section 7 concludes, and additional materials are provided in the appendix.

2. LITERATURE REVIEW

   The role of energy in the residential sector is an important concern for climate policy design, as this sector is often associated with issues such as energy taxation and prices as well as carbon mitigation and redistribution. We first analyze the determinants of C[O.sub.2] emissions in the residential sector and then estimate the consequences of carbon taxation in Europe. For consistency, we have divided the literature review into two parts. The first focuses on energy consumption and C[O.sub.2] emissions in the residential sector, while the second focuses on the distributional effects of carbon taxation.

   2.1 Energy demand and residential C[O.sub.2] emissions

   The literature mainly focuses on residential energy demand, and not specifically on C[O.sub.2] emissions. These two variables are closely linked since the energy mix is predominantly based on fossil fuels and the technologies have remained relatively stable over time (see Table 9 in the appendix). As noted by Kristrom (2008), the key drivers of residential energy demand are (i) prices, (ii) income and (iii) weather conditions. This was confirmed by Du et al. (2021) who analyzed the energy demand in China's urban residential sector over the period 2001-2014.

   First, regarding the role of prices, it is useful to distinguish the short-run from the long-run. Indeed, the demand for energy services is combined with demand for other goods such as capital goods (e.g., devices) to produce an energy service. In the short-run, capital is fixed, and energy demand is inelastic to prices. In the long-run, energy demand becomes more elastic because households can react to a price increase by purchasing more efficient appliances and equipment. Price elasticities vary over time, and by type of fuel and geography, and are always found to be negative, varying from -0.04 to -1.7. Alberini and Filippini (2011) presented an empirical analysis of the residential demand for electricity using state-level annual aggregate data for 48 US States from 1995 to 2007. They obtain a long-run price elasticity of -0.70. Filippini et al. (2014) focused on the EU-27 member states over the period 1996-2009. They estimated the price elasticities of residential energy use to be between -0.26 and -0.19. Our results are clearly in line with these findings, even though we consider C[O.sub.2] emissions and not energy demand per se. Our C[O.sub.2] emissions per capita elasticities relative to energy prices range from -0.25 to -0.1 in the short-run and -0.5 to -0.3 in the long-run.

   Secondly, income also plays an important role in energy demand. Most studies conclude that income elasticity of energy demand is often lower than one, which is consistent with normal-good status even in a long-run perspective. Filippini et al. (2014) obtained an income elasticity of 0.42 for the EU-27 member states over the period 1996-2009. Auffhammer and Wolfram (2014) presented evidence suggesting that the shape of income distribution drives household acquisition of energy-using goods in China. As noted in the literature review by Miller and Alberini (2016) and the meta-analysis of 428 papers in Labandeira et al. (2017), growth in business activity is an important factor affecting energy consumption, particularly over long periods (IEA, 2018).

   Third, weather conditions help explain changes in energy consumption: colder winters increase heating needs, and thus energy consumption (see Mansur et al., 2008; Honore, 2018; and Thomas and Rosenow, 2020).

   Finally, following on from the role of energy prices, energy policies also explain energy demand. Thomas and Rosenow (2020) emphasized that European countries should implement more ambitious policies to improve heating efficiency. (1) Thonipara et al. (2019) studied panel data from the 28 countries of the European Union and Norway over sixteen years and showed that carbon taxation represents an effective means to improve energy efficiency. They found that the carbon tax has two major effects, especially in Sweden: (1) a general reduction in energy consumption and (2) changes in the energy mix. However, a carbon tax of only [euro]4.50 per tonne of C[O.sub.2] as in Latvia or [euro]30 in Finland cannot achieve the far-reaching effects in energy efficiency as observed in Sweden (with a carbon tax of [euro]120 per tonne of C[O.sub.2]).

   2.2 Distributional effects and efficiency of carbon taxation

   There is an extensive literature on the unequal geographic and social burden of carbon taxation (for the U.S. economy, see for example Hasset et al., 2009; Mathur and Morris, 2012; Rausch and Schwarz, 2016). Specifically, regarding the impact of energy taxes on residential energy consumption in the European Union, Borozan (2019) emphasizes two important issues: the heterogeneous consequences of the carbon tax between countries, and also the low efficiency of the tax on residential energy consumption. The author shows that higher energy taxes may increase energy consumption in lower energy-consuming countries. This counterintuitive result can be explained as follows: (1) carbon taxes alone have very little impact on energy consumption, and energy demand is even...